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第30届中国控制与决策会议

作者： Zhaoyuan Jiang Lixin Wang Jiaqiu Song Fucai Liu Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Yanshan University Engineering Training Center

Both sides of the level hydraulic cylinder on internal high pressure forming machine position synchronous system control is one of the key technologies for Internal high pressure forming system, control performance directly affects the production efficiency and product *** on this problem,multivariate coordinated control simulation test platform is be seted up. Mainly includes the control scheme design, control system hardware and software design. The Siemens S7-300 PLC has been as the main controller,WinCC as the upper computer software. Finally based on FM355 C module position synchronization control experiment was carried out by the PID algorithm. the experiment result shows that, in the slope under the condition of smaller FM355 C position synchronization control effect is good, the system can meet the production requirements of internal high pressure forming.

关键词： Paper Internal high pressure forming WinCCSynchronous control S7-300

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Research and Application of Flatness control for Tandem Cold Rolling

Research and Application of Flatness Control for Tandem Cold...

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第37届中国控制会议

作者： LI Xiaogang FANG Yiming LIU Le Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling

Compound wave defect occurs in flatness during tandem cold rolling when high-end automobile and household appliance plate are produced, which has several impact on line speed and quality of final product. In this paper, a further research is done on sourcing cause of formation for the flatness defect. In combination with adjusting actuators and automatic flatness control principles, Achieving target flatness by rolls tilting, work rolls bending, middle rolls bending, and section cooling *** control output of tilting, work rolls and middle rolls bending are calculated by the least square method. Section cooling control output of rolling is calculated by the typical fuzzy control theory. The least square method and fuzzy control algorithm are optimized so as to enhance control accuracy of automatic flatness, and at the same time largely improve flatness of steel strip, reduce working strength of operators and improve production efficiency of production line.

关键词： Tandem cold rolling Automatic flatness control Least square method Fuzzy control

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Fuzzy Q-learning obstacle avoidance algorithm of humanoid robot in unknown environment

Fuzzy Q-learning obstacle avoidance algorithm of humanoid ro...

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Chinese control Conference

作者： Shuhuan Wen Jianhua Chen Zhen Li Ahmad B. Rad Kamal Mohammed Othman Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Engineering Sciences Simon Fraser University Surrey BC Canada

This paper proposes a fuzzy Q-learning (FQL) algorithm to solve the problem of the robot obstacle avoidance in unknown environment. FastSLAM algorithm is used to localize the position of the robot. Traditional Q-learning algorithm, optimized Q-learning algorithm, FQL algorithm are compared. The simulation results show that FQL algorithm has a faster learning speed than other two algorithms and the results demonstrate that the fuzzy Q-learning obstacle avoidance algorithm is effective.

关键词： Collision avoidance Path planning Convergence Humanoid robots Mobile robots Fuzzy sets

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Flatness predictive model based on T-S cloud reasoning network implemented by DSP

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Journal of Central South University 2017年第10期24卷 2222-2230页

作者： ZHANG Xiu-ling GAO Wu-yang LAI Yong-jin CHENG Yan-tao Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan UniversityQinhuangdao 066004China National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan UniversityQinhuangdao 066004China

The accuracy of present flatness predictive method is limited and it just belongs to software simulation. In order to improve it, a novel flatness predictive model via T-S cloud reasoning network implemented by digital signal processor(DSP) is proposed. First, the combination of genetic algorithm(GA) and simulated annealing algorithm(SAA) is put forward, called GA-SA algorithm, which can make full use of the global search ability of GA and local search ability of SA. Later, based on T-S cloud reasoning neural network, flatness predictive model is designed in DSP. And it is applied to 900 HC reversible cold rolling mill. Experimental results demonstrate that the flatness predictive model via T-S cloud reasoning network can run on the hardware DSP TMS320 F2812 with high accuracy and robustness by using GA-SA algorithm to optimize the model parameter.

关键词： T-S cloud reasoning neural network cloud model flatness predictive model hardware implementation digital signal processor genetic algorithm and simulated annealing algorithm (GA-SA)

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An Ameliorated Moth-flame Optimization Algorithm

An Ameliorated Moth-flame Optimization Algorithm

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第37届中国控制会议

作者： Xiao-dong Zhao Yi-ming Fang Zhuang Ma Miao Xu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Tangshan University

To improve the global search ability under the condition of ensuring convergence speed, it is still a major challenge for most meta-heuristic optimization algorithms. The Moth-Flame Optimization（MFO） algorithm is an innovative nature-inspired algorithm. To improve the precision of the solution and to quicken the convergence speed and to increase the stability of MFO,an ameliorated Moth-flame optimization algorithm（A-MFO） that combines the crisscross optimization algorithm with MFO is proposed to solve this problems that are mentioned above. The performance of proposed A-MFO is demonstrated on six benchmark mathematical function optimization problems regarding superior accuracy and lower computational time achieved compared to other well-known nature-inspired algorithms.

关键词： Moth-flame optimization algorithm crisscross optimization algorithm stochastic optimization convergence

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Path Planning of Humanoid Arm Based on Deep Deterministic Policy Gradient

Path Planning of Humanoid Arm Based on Deep Deterministic Po...

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IEEE International Conference on Robotics and Biomimetics

作者： Shuhuan Wen Jianhua Chen Shen Wang Hong Zhang Xueheng Hu department of Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Department of Computing Science University of Alberta Edmonton Canada

ISBN: (纸本)9781728103785;9781728103778

The robot arm with multiple degrees of freedom and working in a 3D space needs to avoid obstacles during the grasping process by its end effector. Path planning to avoid obstacles is very important for accomplishing a grasping task. This paper proposes a new obstacle avoidance algorithm, based on an existing deep reinforcement learning framework called deep deterministic policy gradient (DDPG). Specifically, we propose to use DDPG to plan the trajectory of a robot arm to realize obstacle avoidance. The rewards are designed to overcome the difficulty in convergence of multiple rewards, especially when the rewards are antagonistic with respect to each other. Obstacle avoidance of the robot arm using DDPG is achieved by self-learning, and the convergence problem caused by the high dimension state input and multiple return values is solved. The simulation model of an arm of the Nao robot is built based on the MuJoCo simulation environment. The simulation demonstrates that the proposed algorithm successfully allows the robot arm to avoid obstacles.

关键词： Manipulators Neural networks Robot kinematics Planning Reinforcement learning Trajectory

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Electrochemical Detection of Insulin Based on Screen Printed Electrode Modified by Nickel Hydroxide

Electrochemical Detection of Insulin Based on Screen Printed...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Hongyu Zhang Zhikun Zhan Yuliang Zhao Xiaopeng Sha Xiaodong Yu Hui Sun Lijia Gu Jiali Liu Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

This paper reports a novel electrochemical method for the detection of insulin in ultra-pure water. A screen printed electrode (SPE) modified by Nickel hydroxide was used as the working electrode, one with good activity of electro-catalytic oxidation-reduction for insulin. The SPE was modified by Nickel hydroxide using the electrodeposition method. The results showed that Nickel hydroxide was homogeneously electrodeposited on the surface of the working electrode. A coin-size electrolytic tank was fabricated with PDMS, which only requires 0.3ml of sample for the detection. The concentration of insulin was analyzed using the methods of Cyclic voltammetry (CV), Electrochemical impedance spectroscopy (EIS) and Chronoamperometry (i-t). The Nickel hydroxide used for detecting insulin showed good analytical characteristics, such as a high sensitivity of 14.797μA·μM -1 , a good linear detection range of 100nM-5μM, and a low detection limit of 93nM. This nickel hydroxide modified SPE electrode has a much smaller size and is easier to fabricate than traditional electrodes, making it a much more promising candidate for an insulin sensor.

关键词： Electrodes Insulin Nickel Oxidation Sensitivity Surface treatment Diabetes

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Looseness Detection of Rail Fasteners Using MEMS Sensor and Power Spectrum Entropy

Looseness Detection of Rail Fasteners Using MEMS Sensor and ...

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International Conference on Micro/Nano Sensors for AI, Healthcare, and Robotics (NSENS)

作者： Hao Sun Zhikun Zhan Hongyu Zhang Junshan Liu Xiaopeng Sha Xiaodong Yu Jianing Yu Yuliang Zhao Lianqing Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China State key Laboratory of Robotics Chinese Academy of Sciences

ISBN: (纸本)9781538694091;9781538694084

Rail fasteners, a key component of a railway track, are used to connect the rail and the sub-rail foundation together with the required degree of elasticity. Severely loose or failed fasteners may lead to serious safety hazards for rail transportation. However, current strategies for determining fastener looseness are mainly implemented manually, which is labor-intensive, inefficient and less-than-objective. In this paper, we propose a system that uses a MEMS acceleration meter and a wireless data transmission technique to detect railway fasteners. Vibration was generated by hitting the rail with a hammer. Then the acceleration data was transmitted to the cloud by the Global System for Mobile Communications (GSM) technique. The fastener looseness was analyzed using power spectrum entropy and frequency domain analysis. Results from the field experiments show that our method can identify the fastener's loosening state accurately and automatically. This wireless, low-cost fastener inspection system is expected to provide an effective approach to improving the efficiency of regular railway maintenance..

关键词： Conferences Artificial intelligence Medical services Robot sensing systems IP networks

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Nonlinear control of triple inverted pendulum based on T-S cloud inference network 29

Nonlinear control of triple inverted pendulum based on T-S c...

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第29届中国控制与决策会议

作者： Xiu-ling Zhang Jing-huan Dai Yan-tao Cheng Shuang Hao Jia-huan Li Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University National Engineering Research Center for Equipment and Technology of Cold Strip Rolling Yanshan University

ISBN: (纸本)9781509046584

The triple inverted pendulum is a nonlinear, dynamic and unsteady system. The traditional control methods of triple inverted pendulum have limited control accuracy and slow responding. This kind of pendulum system is difficult to control due to the inherent instability and nonlinear behavior. In this paper, GA-RBF-ARX model is applied to model triple inverted pendulum based on its input/output data. According to the nonlinear identification model, a novel method via T-S cloud inference network controller optimized by genetic algorithm(GA) is proposed. T-S cloud inference network is constituted by T-S fuzzy neural network and the cloud model. Therefore, the rapid of fuzzy logic and the uncertain of cloud model for processing data are both taken into account. What's more, GA possesses global optimization characteristics and good parallel design structure. Compared with the simulation recognition results of T-S fuzzy neural network controller, T-S cloud reference network controller has strong robust and fast calculate speed. So, T-S cloud inference network by GA is an effective method in control.

关键词： T-S cloud inference network GA-RBF-ARX Triple inverted pendulum

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Fuzzy Sliding Mode controller Design for Active Suspension Systems with Load Variation

Fuzzy Sliding Mode Controller Design for Active Suspension S...

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第六届工程机械与车辆工程新进展国际学术会议

作者： S.Liu Z.G.Wang Y.P.Zhang Z.J.Lin Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University

This paper mainly investigates the fuzzy sliding mode control of 1/4 vehicle suspension ***,the dynamical model of suspension system with uncertainty is established for the time-varying of

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